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<p>
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<p>
<strong>Open-source runtime security for AI agents.</strong>
</p>
<p>
Intercept every agent action before execution and decide:
<strong>ALLOW</strong>, <strong>BLOCK</strong>, or <strong>ESCALATE</strong>.
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<a href="https://aegisora-ai.vercel.app"><strong>Live Demo</strong></a>
·
<a href="https://github.com/aegisora-ai/aegisora.ai/blob/main/ARCHITECTURE.md"><strong>Architecture</strong></a>
·
<a href="https://github.com/aegisora-ai/aegisora.ai/blob/main/SECURITY.md"><strong>Security</strong></a>
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<a href="https://discord.gg/8CM3PpQRT5"><strong>Discord</strong></a>
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> **Aegisora sits between your AI agent and the systems it can act on.**
> Every tool call is evaluated at runtime before execution.
---
## Why Aegisora?
AI agents can do more than generate text. They can call tools, access services, execute workflows, and take actions in external systems.
That makes runtime control a security boundary.
Aegisora provides an open-source runtime layer for evaluating agent actions **before execution**, applying governance policies, assessing risk, enforcing permissions, and producing an explicit decision:
**ALLOW · BLOCK · ESCALATE**
The goal is simple:
> **Let agents act — but never let them act without runtime control.**
---
## How It Works
Aegisora is designed to sit directly between an AI agent and the systems it can reach.
```text
┌──────────────────────┐
│ AI AGENT │
└──────────┬───────────┘
│
│ Tool / Action Request
▼
┌───────────────────────────────┐
│ AEGISORA │
│ Runtime Security │
│ │
│ Identity · Permission │
│ Policy · Context · Risk │
└──────────────┬────────────────┘
│
▼
┌───────────────┐
│ DECISION │
└───────┬───────┘
│
┌───────┼────────┐
▼ ▼ ▼
ALLOW BLOCK ESCALATE
│ │ │
└───────┼────────┘
▼
EXECUTION
│
▼
AUDIT / EVIDENCE
```
For the visual architecture overview, see [`ARCHITECTURE.md`](./ARCHITECTURE.md).
<p align="center">
<img
src="assets/architecture.png"
alt="Aegisora runtime architecture"
width="900"
/>
</p>
---
## Core Capabilities
- **Runtime interception** — evaluate agent actions before execution.
- **Policy enforcement** — apply explicit governance rules to agent behavior.
- **Permission control** — restrict what an agent can do and which execution surfaces it can reach.
- **Risk assessment** — evaluate actions in context before they are executed.
- **Decision enforcement** — return `ALLOW`, `BLOCK`, or `ESCALATE`.
- **Zero-trust execution** — treat every agent action as requiring an explicit runtime decision.
- **Audit and evidence** — record security decisions as auditable runtime evidence.
- **Provider-aware governance** — designed to operate across modern AI provider integrations.
---
## Runtime Security Model
Aegisora treats an agent's ability to act as a controlled capability rather than an implicit privilege.
Every request moves through a runtime decision path:
```text
Agent Action
│
▼
┌──────────────┐
│ Interception │
└──────┬───────┘
▼
┌──────────────┐
│ Security │
└──────┬───────┘
▼
┌──────────────┐
│ Policy │
└──────┬───────┘
▼
┌──────────────┐
│ Risk Assess. │
└──────┬───────┘
▼
┌──────────────┐
│ Decision │
└──────┬───────┘
│
┌───┼────────┐
▼ ▼ ▼
ALLOW BLOCK ESCALATE
│
▼
Execution
│
▼
Audit / Evidence
```
This creates a clear enforcement boundary between the agent's reasoning and the external systems it can affect.
---
## Decision Model
Aegisora uses three explicit runtime outcomes:
| Decision | Meaning |
|---|---|
| **ALLOW** | The requested action satisfies the applicable security and governance requirements and may proceed. |
| **BLOCK** | The requested action violates a security or governance requirement and must not execute. |
| **ESCALATE** | The requested action requires additional review, control, or handling before execution. |
The important property is that the decision happens **before the action is executed**.
---
## Risk Classification
Aegisora evaluates agent actions in context rather than treating every tool call as equivalent.
The runtime can use factors such as:
- requested capability,
- selected tool or execution surface,
- applicable policy,
- permissions,
- contextual risk,
- and the consequences of allowing the action.
The result feeds the runtime decision:
```text
LOW / ACCEPTABLE RISK
│
▼
ALLOW
HIGH / DISALLOWED RISK
│
▼
BLOCK
REQUIRES ADDITIONAL CONTROL
│
▼
ESCALATE
```
For the detailed implementation and security model, see [`SECURITY.md`](./SECURITY.md).
---
## Governance Policies
Policies define what an agent is allowed to do at runtime.
A policy can be used to express governance requirements around:
- permitted capabilities,
- restricted actions,
- execution boundaries,
- risk thresholds,
- and escalation conditions.
The intent is to keep governance **explicit, reviewable, and enforceable at runtime** instead of relying only on prompts or application-level conventions.
---
## Audit & Evidence
Runtime decisions should be observable and explainable.
Aegisora records security decisions as audit/evidence data so teams can understand:
```text
WHO
↓
requested WHAT
↓
using WHICH capability
↓
under WHICH policy
↓
with WHICH risk assessment
↓
resulting in WHICH decision
```
This provides a traceable security boundary for agent activity.
---
## Supported Providers
Aegisora is designed to work with modern AI agent stacks and provider integrations.
Current provider integrations include:
- OpenAI
- Anthropic
- Gemini
The runtime model is intended to remain provider-agnostic: the security and governance decision should be enforced at the runtime boundary rather than being tied to a single model provider.
---
## Quick Start
Clone the repository and install the dependencies:
```bash
git clone https://github.com/aegisora-ai/aegisora.ai.git
cd aegisora.ai
pnpm install
```
Start the development environment:
```bash
pnpm dev
```
Then open the local development URL reported by Next.js.
For the live project, see the [Live Demo](https://aegisora-ai.vercel.app).
---
## Project Structure
At a high level, Aegisora is organized around a runtime enforcement path:
```text
Agent
│
▼
Runtime Gateway
│
├── Security
│
├── Policy
│
├── Permission
│
├── Risk Assessment
│
└── Decision
│
├── ALLOW
├── BLOCK
└── ESCALATE
│
▼
Execution
│
▼
Audit / Evidence
```
See [`ARCHITECTURE.md`](./ARCHITECTURE.md) for the detailed architecture.
---
## Examples
### Allow a permitted action
```text
Agent
│
└── Request tool execution
│
▼
Aegisora
│
├── policy: permitted
├── permission: valid
└── risk: acceptable
│
▼
ALLOW
│
▼
Execute
```
### Block a disallowed action
```text
Agent
│
└── Request tool execution
│
▼
Aegisora
│
├── policy: denied
└── risk: unacceptable
│
▼
BLOCK
```
### Escalate an ambiguous action
```text
Agent
│
└── Request tool execution
│
▼
Aegisora
│
├── policy: requires review
└── risk: unresolved
│
▼
ESCALATE
```
---
## Security
Security is a first-class part of the project.
For the detailed security model, threat considerations, and security guidance, see [`SECURITY.md`](./SECURITY.md).
Please do not disclose security-sensitive information in public issues. For responsible disclosure, follow the project's security guidance.
---
## Architecture
The core architectural principle is:
> **Agent → Runtime Gateway → Security → Policy → Decision → Execution**
Aegisora is designed to enforce governance before an agent action crosses into the systems it can affect.
See [`ARCHITECTURE.md`](./ARCHITECTURE.md) for the full architecture documentation.
---
## Roadmap
Aegisora is being developed as an open-source runtime security and governance layer for autonomous AI agents.
The project roadmap focuses on strengthening:
- runtime policy enforcement,
- permission and capability controls,
- contextual risk assessment,
- auditability and evidence,
- provider and tool integrations,
- and production-grade governance.
See the repository's [Issues](https://github.com/aegisora-ai/aegisora.ai/issues) and [Releases](https://github.com/aegisora-ai/aegisora.ai/releases) for the current project status.
---
## Contributing
Contributions are welcome.
Before opening a pull request:
1. Review the existing architecture and security model.
2. Keep runtime enforcement behavior explicit and testable.
3. Add or update tests for security-sensitive changes.
4. Keep documentation aligned with the implementation.
5. Explain the motivation and impact of non-trivial changes.
For project discussion and community collaboration, join the [Aegisora Discord](https://discord.gg/8CM3PpQRT5).
---
## Community
- **GitHub:** https://github.com/aegisora-ai/aegisora.ai
- **Live Demo:** https://aegisora-ai.vercel.app
- **Discord:** https://discord.gg/8CM3PpQRT5
- **Product Hunt:** https://www.producthunt.com/posts/aegisora
---
## License
Aegisora is released under the [MIT License](./LICENSE).
---
<div align="center">
<strong>Aegisora</strong>
<br />
Zero-Trust Security for AI Agents.
<br /><br />
<a href="https://github.com/aegisora-ai/aegisora.ai">
GitHub
</a>
·
<a href="https://aegisora-ai.vercel.app">
Live Demo
</a>
·
<a href="https://discord.gg/8CM3PpQRT5">
Discord
</a>
</div>
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